fig1_theme <- theme(text=element_text(size=8, face="plain"),
                    strip.text=element_text(size=8, face="plain"),
                    plot.title=element_text(size=8, face="plain"),
                    axis.text=element_text(size=8),
                    axis.title=element_text(size=8, face="plain"), 
                    plot.background = element_blank(), 
                    panel.background = element_blank(),
                    legend.text=element_text(size=8),
                    legend.key.size = unit(0.5,"line"),
                    axis.line=element_line(size=0.12),
                    axis.ticks=element_line(size=0.12),
                    legend.margin=margin(t=0, unit='cm'),
                    plot.margin = margin(0.25, 0.25, 0.25, 0.25, "cm"))
fig1a <- readRDS('figures/cell_line_features/Pediatric (CRISPR only)_20q1.rds')
fig1b <- readRDS('figures/tumor_cl/tumor_cl_reannotated_pediatric_2_20q1.rds')
fig1c <- readRDS('figures/mutation/mutsig_rates_in_WES_20q1.rds')
fig1d <- readRDS('figures/mutation/peds_v_other_mutsig_across_lineages_in_WES_20q1.rds')

# decrease size of dots
fig1c$layers[[1]]$aes_params$size <- 1

fig1c$labels$y <- gsub("MutSig2CV ", "MutSig2CV\n", fig1c$labels$y)
fig1d$labels$y <- gsub("MutSig2CV ", "MutSig2CV\n", fig1d$labels$y)

# decrease size of p-value text
fig1d$layers[[3]]$aes_params$textsize <- 2

# decrease size of violin outline
fig1d$layers[[1]]$aes_params$size <- 0
# outlier alpha
fig1d$layers[[2]]$geom_params$outlier.alpha <- 0.25

# decrease size of dots
#fig1b$layers[[1]]$aes_params$size <- 2

# adjust legend
fig1a$guides$fill$nrow <- NULL
fig1a$guides$fill$ncol <- NULL

fig1b$guides$shape$override.aes$size <- 1
fig1b$guides$fill$override.aes$size <- 1
fig1b$labels$title <- "Tumor-cell line expression"
fig1b$guides$fill$title <- "Tumor type"

fig1 <- ggarrange(ggarrange(fig1a + fig1_theme + 
                    theme(legend.position = "right", 
                          axis.text.x=element_text(size=3), 
                          axis.text.y=element_text(size=5), 
                          axis.line=element_blank(),
                          axis.ticks = element_blank()), 
                    geom_blank(),
                    widths = c(2, 0.25),
                    ncol = 2,
                    nrow = 1,
                    labels = c("a", "")),
                  ggarrange(fig1b + fig1_theme + theme(aspect.ratio=1), 
                            geom_blank(),
                            widths = c(2, 0.75),
                            ncol = 2,
                            nrow = 1,
                            labels = c("b", "")),
                  ggarrange(fig1c + fig1_theme, 
                            fig1d + fig1_theme, 
                            widths = c(2, 0.75),
                            ncol = 2, 
                            nrow = 1, 
                            align = "h",
                            labels = c("c", "d")), 
                  nrow =3, 
                  ncol=1,
                  heights = c(3.5, 3, 3))
## Warning in as_grob.default(plot): Cannot convert object of class
## LayerInstanceLayerggprotogg into a grob.

## Warning in as_grob.default(plot): Cannot convert object of class
## LayerInstanceLayerggprotogg into a grob.
ggsave(fig1, filename = "final_figures/Fig1.pdf", width=20 , height=26, units='cm', useDingbats = FALSE)
print(fig1)

fig2a <- readRDS('figures/dependency/dep_example_distribution_20q1.rds')
fig2b <- readRDS('figures/mutation/depsLRT_v_mutsig_across_lineages_in_WES_20q1.rds')
fig2c <- readRDS('figures/dependency/total_lrt_dependencies_median_arranged_20q1.rds')
fig2d <- readRDS('figures/dependency/peds_v_other_LRTdeps_all_20q1.rds')
fig2e <- readRDS('figures/biomarkers/lrt_rate_vs_biomarker_20q1.rds')
fig2f <- readRDS('figures/dependency/umap_cell_line_dependency_lrt_20q1.rds')

# decrease size of lines
fig2a$labels$y <- "Distribution of cell lines"
fig2a$layers[[2]]$aes_params$size <- 4

# decrease size of dots
fig2b$layers[[1]]$aes_params$size <- 1
fig2b$labels$y <- gsub("MutSig2CV ", "MutSig2CV\n", fig2b$labels$y)

# decrease size of dots
fig2c$layers[[1]]$aes_params$size <- 1

# decrease size of p-value text
fig2d$layers[[3]]$aes_params$textsize <- 2
fig2d$layers[[3]]$aes_params$size <- 2

# decrease size of violin outline
fig2d$layers[[1]]$aes_params$size <- 0
fig2d$layers[[2]]$geom_params$outlier.alpha <- 0.25

fig2d$labels$y <- fig2c$labels$y

fig2e$labels$title <- "Predictive models"

# decrease size of dots
fig2f$layers[[1]]$aes_params$size <- 2
fig2f$labels$title <- "Dependency embedding"

fig2 <- ggarrange(ggarrange(fig2a + fig1_theme,
                            fig2b + fig1_theme + theme(aspect.ratio=1),
                            widths = c(2, 3),
                            ncol = 2,
                            nrow = 1,
                            labels = c("a", "b")),
                  ggarrange(fig2c + fig1_theme, 
                            fig2d + fig1_theme, 
                            widths = c(2, 0.75),
                            ncol = 2, 
                            nrow = 1, 
                            align = "h",
                            labels = c("c", "d")), 
                  ggarrange(fig2e + fig1_theme + theme(aspect.ratio=1, legend.position = "bottom"), 
                            ggarrange(fig2f + fig1_theme + theme(aspect.ratio=1, legend.position = "right"), geom_blank(),
                                      heights = c(2, 0.3),
                                      ncol = 1,
                                      nrow = 2),
                            widths = c(2, 3.5),
                            ncol = 2,
                            nrow = 1,
                            align = "h",
                            labels = c("e", "f")),
                  nrow =3, 
                  ncol=1,
                  heights = c(3, 3, 3.5),
                  align = "v")
## Warning in as_grob.default(plot): Cannot convert object of class
## LayerInstanceLayerggprotogg into a grob.
## Warning: Graphs cannot be horizontally aligned unless the axis parameter is set.
## Placing graphs unaligned.
ggsave(fig2, filename = "final_figures/Fig2.pdf", width=20 , height=26, units='cm', useDingbats = FALSE)
print(fig2)

fig3a <- readRDS('figures/targets/dep_heatmap_horz_ALK_20q1.rds')
fig3b <- readRDS('figures/targets/dep_heatmap_horz_BRAF_20q1.rds')
fig3c <- readRDS('figures/targets/dep_heatmap_horz_MDM2_MDM4_20q1.rds')
fig3d <- readRDS('figures/targets/dep_heatmap_horz_CDK4_CDK6_20q1.rds')
fig3e <- readRDS('figures/targets/dep_heatmap_horz_BCL2_MCL1_20q1.rds')
fig3_legend1 <- readRDS('figures/targets/dep_heatmap_horz_legend1_20q1.rds')
fig3_legend2 <- readRDS('figures/targets/dep_heatmap_horz_legend2_20q1.rds')

font_for_grob <- 3
names(font_for_grob) <- "italics"

for (i in 1:length(fig3_legend2$gtable[["grobs"]][[3]]$children))
{
  if (!is.null(fig3_legend2$gtable[["grobs"]][[3]]$children[[i]]$label))
  {
    cat(i)
    fig3_legend2$gtable[["grobs"]][[3]]$children[[i]]$label <- gsub("biomarker", "Biomarker", fig3_legend2$gtable[["grobs"]][[3]]$children[[i]]$label)
    fig3_legend2$gtable[["grobs"]][[3]]$children[[i]]$label <- gsub("tumor_type", "Tumor type", fig3_legend2$gtable[["grobs"]][[3]]$children[[i]]$label)
  }
  if (!is.null(fig3_legend2$gtable[["grobs"]][[3]]$children[[i]]$gp$fontface))
  {
    if (fig3_legend2$gtable[["grobs"]][[3]]$children[[i]]$gp$fontface == "bold")
    {
      fig3_legend2$gtable[["grobs"]][[3]]$children[[i]]$gp$fontface <- "italics"
      fig3_legend2$gtable[["grobs"]][[3]]$children[[i]]$gp$font <- as.integer(font_for_grob)
    }
  }
}
## 1346
library("gridExtra")
lay <- rbind(c(1,6),
             c(2,7),
             c(3,NA),
             c(4,NA),
             c(5,NA))

fig3_heatmaps <- arrangeGrob(fig3a[[4]], 
                             fig3b[[4]],
                             fig3c[[4]], 
                             fig3d[[4]],
                             fig3e[[4]],
                             fig3_legend1[[4]],
                             fig3_legend2[[4]],
                             layout_matrix = lay,
                             widths=c(4, 0.6),
                             padding = unit(0.25, "cm"))

ggsave(fig3_heatmaps, filename = "final_figures/Fig3.pdf", width=35, height=30, units='cm', useDingbats = FALSE)
grid.draw(fig3_heatmaps)

fig3f <- readRDS('figures/mcl1_compare/depmap_sanger_20q1.rds')

fig3f$layers[[1]]$aes_params$size <- 1

fig3f <- ggarrange(ggarrange(fig3f + fig1_theme + theme(aspect.ratio=1), 
                             geom_blank(), 
                             ncol = 2,
                             align="h",
                             widths=c(1,1),
                             labels = c("f", "g")),
                     geom_blank(),
                     nrow=2, 
                     ncol=1,
                     heights  = c(2, 4))
## Warning in as_grob.default(plot): Cannot convert object of class
## LayerInstanceLayerggprotogg into a grob.
## Warning: Graphs cannot be horizontally aligned unless the axis parameter is set.
## Placing graphs unaligned.
## Warning in as_grob.default(plot): Cannot convert object of class
## LayerInstanceLayerggprotogg into a grob.
ggsave(fig3f, filename = "final_figures/Fig3f.pdf", width=20 , height=26, units='cm', useDingbats = FALSE)
print(fig3f)

fig4a <- readRDS('figures/dependency/ped_v_adult_fraction_dependent_20q1.rds')
fig4b <- readRDS('figures/dependency/ped_v_adult_sig_fraction_dependent_20q1.rds')
fig4c_TRIM8_p <- readRDS('figures/dependency/gene_TRIM8_peds_20q1.rds')
fig4c_TRIM8_a <- readRDS('figures/dependency/gene_TRIM8_adult_20q1.rds')
fig4c_HDAC2_p <- readRDS('figures/dependency/gene_HDAC2_peds_20q1.rds')
fig4c_HDAC2_a <- readRDS('figures/dependency/gene_HDAC2_adult_20q1.rds')
fig4c_IGF1R_p <- readRDS('figures/dependency/gene_IGF1R_peds_20q1.rds')
fig4c_IGF1R_a <- readRDS('figures/dependency/gene_IGF1R_adult_20q1.rds')
fig4c_legend_p <- readRDS('figures/dependency/gene_legend_peds_20q1.rds')
fig4c_legend_a <- readRDS('figures/dependency/gene_legend_adult_20q1.rds')

fig4c_TRIM8_a$labels$y <- "Adult"
fig4c_HDAC2_a$labels$y <- ""
fig4c_IGF1R_a$labels$y <- ""
fig4c_TRIM8_p$labels$y <- "Pediatric"
fig4c_HDAC2_p$labels$y <- ""
fig4c_IGF1R_p$labels$y <- ""

fig4c_TRIM8_a$labels$x <- ""
fig4c_HDAC2_a$labels$x <- ""
fig4c_IGF1R_a$labels$x <- ""
fig4c_TRIM8_p$labels$x <- "TRIM8"
fig4c_HDAC2_p$labels$x <- "HDAC2"
fig4c_IGF1R_p$labels$x <- "IGF1R"

fig4c_theme <- theme(plot.margin = margin(-0.5, -0.5, 0, -0.5, "cm"),
                       axis.title  = element_text(size=8, face="plain"),
                       plot.background = element_blank())

fig4d <- readRDS('figures/dependency/peds_LRT_deps_GSEA_C5_20q1.rds')
## 
## Registered S3 method overwritten by 'enrichplot':
##   method               from
##   fortify.enrichResult DOSE
fig4e <- readRDS('figures/dependency/adult_LRT_deps_GSEA_C5_20q1.rds')

fig4d$labels$title <- "Pediatric selective dependencies"
fig4e$labels$title <- "Adult selective dependencies"

fig4f <- readRDS('figures/dependency/peds_enriched_deps_-0.2_20q1.rds')

fig4 <- ggarrange(ggarrange(fig4a + fig1_theme,
                            fig4b + fig1_theme + 
                              theme(axis.text.y = element_text(size=4)),
                            nrow=1,
                            ncol=2,
                            align = "h",
                            labels = c("a", "b")),
                  ggarrange(
                    ggarrange(fig4c_TRIM8_p + fig4c_theme , 
                              fig4c_HDAC2_p + fig4c_theme, 
                              fig4c_IGF1R_p + fig4c_theme, 
                              fig4c_TRIM8_a + fig4c_theme,
                              fig4c_HDAC2_a + fig4c_theme,
                              fig4c_IGF1R_a + fig4c_theme,
                              nrow=2, ncol=3,
                              align="hv") + theme(plot.margin = margin(0.25, 0.25, 0.25, 1, "cm")),
                    ggarrange(fig4c_legend_p, geom_blank(), ncol=1, heights=c(1, 2.6)),
                    ggarrange(fig4c_legend_a, geom_blank(), ncol=1, heights=c(1, 0.05)),
                    nrow=1,
                    widths= c(2,1,1),
                    align="h",
                    labels = c("c", "", "")),
                  ggarrange(
                    ggarrange(fig4d + fig1_theme + theme(axis.text.y = element_text(size=4)) + scale_size(range = c(0,3)), 
                              fig4e + fig1_theme + theme(axis.text.y = element_text(size=4)) + scale_size(range = c(0,3)), 
                              nrow=2, ncol=1, heights = c(1,1), align="v",
                              labels = c("d", "e")),
                    fig4f + fig1_theme + theme(legend.position = "bottom"),
                    ncol = 2,
                    widths = c(1.5, 1),
                    labels = c("", "f")),
                  nrow=3, 
                  ncol=1,
                  heights  = c(2, 1.5, 3))
## Warning in as_grob.default(plot): Cannot convert object of class
## LayerInstanceLayerggprotogg into a grob.

## Warning in as_grob.default(plot): Cannot convert object of class
## LayerInstanceLayerggprotogg into a grob.
## Scale for 'size' is already present. Adding another scale for 'size', which
## will replace the existing scale.
## Scale for 'size' is already present. Adding another scale for 'size', which
## will replace the existing scale.
ggsave(fig4, filename = "final_figures/Fig4.pdf", width=20 , height=26, units='cm', useDingbats = FALSE)
print(fig4)

extfig1_1 <- readRDS('figures/tumor_cl/tumor_cl_reannotated_2_Ewing20q1.rds')
extfig1_2 <- readRDS('figures/tumor_cl/tumor_cl_reannotated_2_Hepatoblastoma20q1.rds')
extfig1_3 <- readRDS('figures/tumor_cl/tumor_cl_reannotated_2_Medulloblastoma20q1.rds')
extfig1_4 <- readRDS('figures/tumor_cl/tumor_cl_reannotated_2_Neuroblastoma20q1.rds')
extfig1_5 <- readRDS('figures/tumor_cl/tumor_cl_reannotated_2_Osteosarcoma20q1.rds')
extfig1_6 <- readRDS('figures/tumor_cl/tumor_cl_reannotated_2_Pediatric CNS PNET20q1.rds')
extfig1_7 <- readRDS('figures/tumor_cl/tumor_cl_reannotated_2_Pediatric Germ Cell20q1.rds')
extfig1_8 <- readRDS('figures/tumor_cl/tumor_cl_reannotated_2_Pediatric Glioma20q1.rds')
extfig1_9 <- readRDS('figures/tumor_cl/tumor_cl_reannotated_2_Pediatric Sarcoma20q1.rds')
extfig1_10 <- readRDS('figures/tumor_cl/tumor_cl_reannotated_2_Renal Medullary Carcinoma20q1.rds')
extfig1_11 <- readRDS('figures/tumor_cl/tumor_cl_reannotated_2_Retinoblastoma20q1.rds')
extfig1_12 <- readRDS('figures/tumor_cl/tumor_cl_reannotated_2_Rhabdoid20q1.rds')
extfig1_13 <- readRDS('figures/tumor_cl/tumor_cl_reannotated_2_Rhabdomyosarcoma20q1.rds')
extfig1_14 <- readRDS('figures/tumor_cl/tumor_cl_reannotated_2_Synovial Sarcoma20q1.rds')

for(plot_to_mod in seq(1, 14, 1))
{
  # decrease size of dots
  #eval(parse(text=paste0("extfig1_", plot_to_mod, "$layers[[1]]$aes_params$size <- 2")))
  
  # decrease size of text labels and change alpha
  eval(parse(text=paste0("extfig1_", plot_to_mod, "$layers[[2]]$aes_params$size <- 1")))
  eval(parse(text=paste0("extfig1_", plot_to_mod, "$layers[[2]]$aes_params$alpha <- 1")))
  
  # change label seg line size and alpha 
  eval(parse(text=paste0("extfig1_", plot_to_mod, "$layers[[2]]$geom_params$segment.size <- 0.2")))
  eval(parse(text=paste0("extfig1_", plot_to_mod, "$layers[[2]]$geom_params$segment.alpha <- 0.5")))

  # modify legend
  eval(parse(text=paste0("extfig1_", plot_to_mod, "$guides$shape$override.aes$size <- 2")))
  eval(parse(text=paste0("extfig1_", plot_to_mod, "$guides$fill$override.aes$size <- 2")))
  
  # remove title
  eval(parse(text=paste0("extfig1_", plot_to_mod, "$labels$title <- NULL")))
  
  if((plot_to_mod - 1) %% 3 != 0)
  {
    eval(parse(text=paste0("extfig1_", plot_to_mod, "$labels$y <- NULL")))
  }
  
  eval(parse(text=paste0("extfig1_", plot_to_mod, "$labels$x <- NULL")))
}

extfig1_theme <- theme(aspect.ratio=1, legend.text = element_text(size=6), legend.title = element_text(size=6), legend.position = c(1,1))

extfig1 <- ggarrange(extfig1_1 + fig1_theme + extfig1_theme, 
                     extfig1_2 + fig1_theme + extfig1_theme, 
                     extfig1_3 + fig1_theme + extfig1_theme, 
                     extfig1_4 + fig1_theme + extfig1_theme, 
                     extfig1_5 + fig1_theme + extfig1_theme, 
                     extfig1_6 + fig1_theme + extfig1_theme, 
                     extfig1_7 + fig1_theme + extfig1_theme, 
                     extfig1_8 + fig1_theme + extfig1_theme, 
                     extfig1_9 + fig1_theme + extfig1_theme, 
                     extfig1_10 + fig1_theme + extfig1_theme, 
                     extfig1_11 + fig1_theme + extfig1_theme, 
                     extfig1_12 + fig1_theme + extfig1_theme, 
                     extfig1_13 + fig1_theme + extfig1_theme, 
                     extfig1_14 + fig1_theme + extfig1_theme, 
                  nrow=5, 
                  ncol=3, 
                  align="v")

ggsave(extfig1, filename = "final_figures/extFig1.pdf", width=20 , height=26, units='cm', useDingbats = FALSE)
print(extfig1)

extfig2a <- readRDS('figures/tumor_cl/undiff_tumor_cl_rennotated_pediatrics_all20q1.rds')
extfig2b <- readRDS('figures/tumor_cl/tumor_cl_reannotated_uncorrected20q1.rds')
extfig2c <- readRDS('figures/mutation/total_mutations_across_lineages_in_WES_20q1.rds')
extfig2d <- readRDS('figures/mutation/peds_v_other_total_mutations_across_lineages_in_WES_20q1.rds')
extfig2e <- readRDS('figures/mutation/total_COSMICgenefiltered_mutations_across_lineages_in_WES_20q1.rds')
extfig2f <- readRDS('figures/mutation/peds_v_other_COSMICgene_mutations_across_lineages_in_WES_20q1.rds')

# decrease size of dots
extfig2c$layers[[1]]$aes_params$size <- 1
extfig2d$layers[[1]]$aes_params$size <- 1
extfig2e$layers[[1]]$aes_params$size <- 1
extfig2f$layers[[1]]$aes_params$size <- 1

# decrease size of p-value text
extfig2d$layers[[3]]$aes_params$textsize <- 2
extfig2f$layers[[3]]$aes_params$textsize <- 2

# decrease size of dots
#extfig2a$layers[[1]]$aes_params$size <- 1
#extfig2b$layers[[1]]$aes_params$size <- 1

extfig2a$guides$shape$override.aes$size <- 1
extfig2a$guides$fill <- FALSE
extfig2a$labels$title <- "Tumor-cell line expression"
extfig2a$guides$shape$nrow <- 8
extfig2a$guides$shape$title.position <- "top"

extfig2b$guides$shape <- FALSE
extfig2b$guides$fill$override.aes$size <- 1
extfig2b$labels$title <- "Tumor-cell line expression"
extfig2b$guides$fill$title <- "Tumor type"
extfig2b$guides$fill$nrow <- 8
extfig2b$guides$fill$title.position <- "top"

# decrease size of violin outline
extfig2d$layers[[1]]$aes_params$size <- 0
extfig2d$layers[[2]]$geom_params$outlier.alpha <- 0.25
extfig2f$layers[[1]]$aes_params$size <- 0
extfig2f$layers[[2]]$geom_params$outlier.alpha <- 0.25

extfig2 <- ggarrange(
                  ggarrange(extfig2a + fig1_theme + theme(aspect.ratio=1, legend.position = "bottom"), 
                            extfig2b + fig1_theme + theme(aspect.ratio=1, legend.position = "bottom"),
                            widths = c(2, 2),
                            ncol = 2,
                            nrow = 1, 
                            align = "h",
                            labels = c("a", "b")),
                  ggarrange(extfig2c + fig1_theme, 
                            extfig2d + fig1_theme, 
                            widths = c(2, 0.75),
                            ncol = 2, 
                            nrow = 1, 
                            align = "h",
                            labels = c("c", "d")),
                  ggarrange(extfig2e + fig1_theme, 
                            extfig2f + fig1_theme, 
                            widths = c(2, 0.75),
                            ncol = 2, 
                            nrow = 1, 
                            align = "h",
                            labels = c("e", "f")), 
                  nrow =3, 
                  ncol=1,
                  heights = c(3.5, 2.5, 2.5))

ggsave(extfig2, filename = "final_figures/extFig2.pdf", width=20 , height=26, units='cm', useDingbats = FALSE)
print(extfig2)

extfig3a <- readRDS('figures/copy_number/cna_by_lineage_plot20q1.rds')
extfig3b <- readRDS('figures/copy_number/peds_v_adult_cna_plot20q1.rds')
extfig3c <- readRDS('figures/copy_number/pediatric_cn_across_lines20q1.rds')
extfig3d <- readRDS('figures/copy_number/fusions_by_lineage_plot20q1.rds')
extfig3e <- readRDS('figures/copy_number/peds_v_adult_fusion_plot20q1.rds')

# decrease size of dots
extfig3a$layers[[1]]$aes_params$size <- 1
extfig3d$layers[[1]]$aes_params$size <- 1

# decrease size of p-value text
extfig3b$layers[[3]]$aes_params$textsize <- 2
extfig3e$layers[[3]]$aes_params$textsize <- 2

# decrease size of violin outline
extfig3b$layers[[1]]$aes_params$size <- 0
extfig3b$layers[[2]]$geom_params$outlier.alpha <- 0.25
extfig3e$layers[[1]]$aes_params$size <- 0
extfig3e$layers[[2]]$geom_params$outlier.alpha <- 0.25

extfig3 <- ggarrange(
                  ggarrange(extfig3a + fig1_theme, 
                            extfig3b + fig1_theme, 
                            widths = c(2, 0.75),
                            ncol = 2, 
                            nrow = 1, 
                            align = "h",
                            labels = c("a", "b")), 
                  extfig3c,
                  ggarrange(extfig3d + fig1_theme, 
                            extfig3e + fig1_theme, 
                            widths = c(2, 0.75),
                            ncol = 2, 
                            nrow = 1, 
                            align = "h",
                            labels = c("d", "e")), 
                  nrow =3, 
                  ncol=1,
                  heights = c(3, 3, 3),
                  labels = c("", "c", ""))

ggsave(extfig3, filename = "final_figures/extFig3.pdf", width=20 , height=26, units='cm', useDingbats = FALSE)
print(extfig3)

extfig4a <- readRDS('figures/mutation/depsLRT_v_total_mutations_across_lineages_in_WES_20q1.rds')
extfig4b <- readRDS('figures/mutation/depsLRT_v_total_COSMICgene_mutations_across_lineages_in_WES_20q1.rds')
extfig4c <- readRDS('figures/copy_number/depsLRT_v_cnas_across_lineages_20q1.rds')
extfig4d <- readRDS('figures/copy_number/depsLRT_v_fusions_across_lineages_20q1.rds')
extfig4e <- readRDS('figures/dependency/total_lrt_dependencies_lineage_size_arranged_20q1.rds')

# decrease size of dots
extfig4a$layers[[1]]$aes_params$size <- 1
extfig4b$layers[[1]]$aes_params$size <- 1
extfig4c$layers[[1]]$aes_params$size <- 1
extfig4d$layers[[1]]$aes_params$size <- 1
extfig4e$layers[[1]]$aes_params$size <- 1

extfig4 <- ggarrange(ggarrange(extfig4a + fig1_theme + theme(aspect.ratio=1), 
                               extfig4b + fig1_theme + theme(aspect.ratio=1), 
                               ncol = 2,
                               nrow = 1,
                               align = "h",
                               labels = c("a", "b")),
                     ggarrange(extfig4c + fig1_theme + theme(aspect.ratio=1), 
                               extfig4d + fig1_theme + theme(aspect.ratio=1), 
                               ncol = 2,
                               nrow = 1,
                               align = "h",
                               labels = c("c", "d")),
                     ggarrange(extfig4e + fig1_theme,
                               geom_blank(), 
                               widths = c(2, 0.75),
                               ncol = 2, 
                               nrow = 1, 
                               align = "h",
                               labels = c("e", "")),  
                     nrow =3, 
                     ncol=1,
                     heights = c(3, 3, 3.5))
## Warning in as_grob.default(plot): Cannot convert object of class
## LayerInstanceLayerggprotogg into a grob.
## Warning: Graphs cannot be horizontally aligned unless the axis parameter is set.
## Placing graphs unaligned.
ggsave(extfig4, filename = "final_figures/extFig4.pdf", width=20 , height=26, units='cm', useDingbats = FALSE)
print(extfig4)

extfig5a <- readRDS('figures/mutation/deps_v_NNMD_20q1.rds')
extfig5b <- readRDS('figures/mutation/deps_v_Cas9_20q1.rds')
extfig5c <- readRDS('figures/mutation/deps_v_growth_20q1.rds')
extfig5d <- readRDS('figures/mutation/deps_v_FDR_TPM0_20q1.rds')
extfig5e <- readRDS('figures/mutation/deps_v_media_20q1.rds')
extfig5f <- readRDS('figures/mutation/deps_v_mets_20q1.rds')
extfig5g <- readRDS('figures/mutation/deps_v_tx_20q1.rds')

# decrease size of dots
extfig5a$layers[[1]]$aes_params$size <- 1
extfig5b$layers[[1]]$aes_params$size <- 1
extfig5c$layers[[1]]$aes_params$size <- 1
extfig5d$layers[[1]]$aes_params$size <- 1
extfig5e$layers[[1]]$aes_params$size <- 1
extfig5f$layers[[1]]$aes_params$size <- 1
extfig5g$layers[[1]]$aes_params$size <- 1

# decrease size of violin outline
extfig5e$layers[[1]]$aes_params$size <- 0
extfig5e$layers[[2]]$geom_params$outlier.alpha <- 0.25
extfig5f$layers[[1]]$aes_params$size <- 0
extfig5f$layers[[2]]$geom_params$outlier.alpha <- 0.25
extfig5g$layers[[1]]$aes_params$size <- 0
extfig5g$layers[[2]]$geom_params$outlier.alpha <- 0.25

extfig5 <- ggarrange(ggarrange(extfig5a + fig1_theme + theme(aspect.ratio=1), 
                               extfig5b + fig1_theme + theme(aspect.ratio=1), 
                               ncol = 2,
                               nrow = 1,
                               align = "h",
                               labels = c("a", "b")),
                     ggarrange(extfig5c + fig1_theme + theme(aspect.ratio=1), 
                               extfig5d + fig1_theme + theme(aspect.ratio=1), 
                               ncol = 2,
                               nrow = 1,
                               align = "h",
                               labels = c("c", "d")),
                     ggarrange(extfig5e + fig1_theme + theme(aspect.ratio=1), 
                               extfig5f + fig1_theme + theme(aspect.ratio=1), 
                               extfig5g + fig1_theme + theme(aspect.ratio=1), 
                               ncol = 3,
                               nrow = 1,
                               align = "h",
                               labels = c("e", "f", "g")),
                     nrow =3, 
                     ncol=1,
                     heights = c(3, 3, 3))
## Warning in wilcox.test.default(c(35, 23, 19, 19, 28, 30, 18, 29, 23, 28, :
## cannot compute exact p-value with ties
## Warning in wilcox.test.default(c(35, 23, 19, 19, 28, 30, 18, 29, 23, 28, :
## cannot compute exact p-value with ties
## Warning in wilcox.test.default(c(19, 24, 19, 27, 22, 22, 39, 29, 14, 36, :
## cannot compute exact p-value with ties
ggsave(extfig5, filename = "final_figures/extFig5.pdf", width=20 , height=26, units='cm', useDingbats = FALSE)
print(extfig5)

extfig6a <- readRDS('figures/biomarkers/pearson_dist_lrt_genes_20q1.rds')
extfig6b <- readRDS('figures/biomarkers/biomarker_peds_vs_all_20q1.rds')

extfig6 <- ggarrange(extfig6a + fig1_theme,
                     ggarrange(extfig6b + fig1_theme + theme(aspect.ratio=1),
                               geom_blank(),
                               nrow=1,
                               ncol=2,
                               widths = c(3,1)),
                     geom_blank(),
                     nrow=3, 
                     ncol=1,
                     heights = c(2, 4, 3),
                     align = "v",
                     labels = c("a", "b", ""))
## Warning in as_grob.default(plot): Cannot convert object of class
## LayerInstanceLayerggprotogg into a grob.

## Warning in as_grob.default(plot): Cannot convert object of class
## LayerInstanceLayerggprotogg into a grob.
## Warning: Graphs cannot be vertically aligned unless the axis parameter is set.
## Placing graphs unaligned.
ggsave(extfig6, filename = "final_figures/extFig6.pdf", width=20 , height=26, units='cm', useDingbats = FALSE)
print(extfig6)

extfig7a <- readRDS('figures/dependency/umap_zoom_peds_colored_cell_line_dependency_lrt_20q1.rds')
extfig7b <- readRDS('figures/dependency/expr_clus_v_dep_clus_dep500_expr_2000_20q1.rds')
extfig7c <- readRDS('figures/expression/expr_lineage_similarity_top_2000_20q1.rds')
extfig7d <- readRDS('figures/expression/expression_pcs_dist_to_center_top2000_20q1.rds')
extfig7e <- readRDS('figures/dependency/dep_lineage_similarity_top_500_20q1.rds')
extfig7f <- readRDS('figures/dependency/dep_pcs_dist_to_center_top500_20q1.rds')

# decrease size of dots
extfig7a$layers[[1]]$aes_params$size <- 2
extfig7a$labels$title <- "Dependency embedding"
extfig7a$layers[[2]]$aes_params$size <- 1
extfig7a$layers[[2]]$geom_params$segment.size <- 0.2
extfig7a$layers[[2]]$geom_params$segment.alpha <- 0.5

# decrease size of dots
extfig7b$layers[[1]]$aes_params$size <- 1
extfig7c$layers[[1]]$aes_params$size <- 1
extfig7d$layers[[1]]$aes_params$size <- 1
extfig7e$layers[[1]]$aes_params$size <- 1
extfig7f$layers[[1]]$aes_params$size <- 1

extfig7 <- ggarrange(ggarrange(extfig7a + fig1_theme + theme(aspect.ratio=1, legend.text = element_text(size=6)), 
                               extfig7b + fig1_theme + theme(aspect.ratio=1),
                               nrow=1,
                               labels = c("a", "b")),
                     ggarrange(extfig7c + fig1_theme, extfig7d + fig1_theme, nrow=1, widths = c(2,2),
                               labels = c("c", "d")),
                     ggarrange(extfig7e + fig1_theme, extfig7f + fig1_theme, nrow=1, widths = c(2,2),
                               labels = c("e", "f")), 
                     nrow =3, 
                     ncol=1,
                     heights = c(4, 2.5, 2.5))

ggsave(extfig7, filename = "final_figures/extFig7.pdf", width=20 , height=26, units='cm', useDingbats = FALSE)
print(extfig7)

extfig8a <- readRDS('figures/mcl1_compare/depmap_demeter_drive_20q1.rds')
extfig8b <- readRDS('figures/biomarkers/pred_features_scatter_MCL1_BCL2L120q1.rds')

extfig8a$layers[[1]]$aes_params$size <- 1
extfig8b$layers[[1]]$aes_params$size <- 1

extfig8 <- ggarrange(ggarrange(extfig8a + fig1_theme + theme(aspect.ratio=1), 
                               extfig8b + fig1_theme + theme(aspect.ratio=1), 
                               ncol = 2,
                               align="h",
                               labels = c("a", "b")),
                     geom_blank(),
                     geom_blank(),
                     geom_blank(),
                     nrow=4, 
                     ncol=1,
                     heights  = c(2, 2, 2, 2),
                     labels = c("", "c", "d", "e"))
## Warning in as_grob.default(plot): Cannot convert object of class
## LayerInstanceLayerggprotogg into a grob.

## Warning in as_grob.default(plot): Cannot convert object of class
## LayerInstanceLayerggprotogg into a grob.

## Warning in as_grob.default(plot): Cannot convert object of class
## LayerInstanceLayerggprotogg into a grob.
ggsave(extfig8, filename = "final_figures/extFig8.pdf", width=20 , height=26, units='cm', useDingbats = FALSE)
print(extfig8)

extfig9a_ISL1_p <- readRDS('figures/dependency/gene_ISL1_peds_20q1.rds')
extfig9a_ISL1_a <- readRDS('figures/dependency/gene_ISL1_adult_20q1.rds')
extfig9a_HAND2_p <- readRDS('figures/dependency/gene_HAND2_peds_20q1.rds')
extfig9a_HAND2_a <- readRDS('figures/dependency/gene_HAND2_adult_20q1.rds')
extfig9a_GATA3_p <- readRDS('figures/dependency/gene_GATA3_peds_20q1.rds')
extfig9a_GATA3_a <- readRDS('figures/dependency/gene_GATA3_adult_20q1.rds')
extfig9a_legend_p <- readRDS('figures/dependency/gene_legend_peds_20q1.rds')
extfig9a_legend_a <- readRDS('figures/dependency/gene_legend_adult_20q1.rds')

extfig9a_ISL1_a$labels$y <- "Adult"
extfig9a_HAND2_a$labels$y <- ""
extfig9a_GATA3_a$labels$y <- ""
extfig9a_ISL1_p$labels$y <- "Pediatric"
extfig9a_HAND2_p$labels$y <- ""
extfig9a_GATA3_p$labels$y <- ""

extfig9a_ISL1_a$labels$x <- ""
extfig9a_HAND2_a$labels$x <- ""
extfig9a_GATA3_a$labels$x <- ""
extfig9a_ISL1_p$labels$x <- "ISL1"
extfig9a_HAND2_p$labels$x <- "HAND2"
extfig9a_GATA3_p$labels$x <- "GATA3"

extfig9a_PHOX2A_p <- readRDS('figures/dependency/gene_PHOX2A_peds_20q1.rds')
extfig9a_PHOX2A_a <- readRDS('figures/dependency/gene_PHOX2A_adult_20q1.rds')
extfig9a_PHOX2B_p <- readRDS('figures/dependency/gene_PHOX2B_peds_20q1.rds')
extfig9a_PHOX2B_a <- readRDS('figures/dependency/gene_PHOX2B_adult_20q1.rds')
extfig9a_MYOD1_p <- readRDS('figures/dependency/gene_MYOD1_peds_20q1.rds')
extfig9a_MYOD1_a <- readRDS('figures/dependency/gene_MYOD1_adult_20q1.rds')

extfig9a_PHOX2A_a$labels$y <- "Adult"
extfig9a_PHOX2B_a$labels$y <- ""
extfig9a_MYOD1_a$labels$y <- ""
extfig9a_PHOX2A_p$labels$y <- "Pediatric"
extfig9a_PHOX2B_p$labels$y <- ""
extfig9a_MYOD1_p$labels$y <- ""

extfig9a_PHOX2A_a$labels$x <- ""
extfig9a_PHOX2B_a$labels$x <- ""
extfig9a_MYOD1_a$labels$x <- ""
extfig9a_PHOX2A_p$labels$x <- "PHOX2A"
extfig9a_PHOX2B_p$labels$x <- "PHOX2B"
extfig9a_MYOD1_p$labels$x <- "MYOD1"

extfig9a_theme <- theme(plot.margin = margin(-0.5, -0.5, 0, -0.5, "cm"),
                       axis.title  = element_text(size=8, face="plain"),
                       plot.background = element_blank())

extfig9b <- readRDS('figures/biomarkers/pred_features_HDAC2 (3066)20q1.rds')
extfig9c <- readRDS('figures/biomarkers/pred_features_IGF1R (3480)20q1.rds')

extfig9 <- ggarrange(ggarrange(
                              ggarrange(extfig9a_ISL1_p + extfig9a_theme , 
                                         extfig9a_HAND2_p + extfig9a_theme, 
                                         extfig9a_GATA3_p + extfig9a_theme, 
                                         extfig9a_ISL1_a + extfig9a_theme,
                                         extfig9a_HAND2_a + extfig9a_theme,
                                         extfig9a_GATA3_a + extfig9a_theme,
                                         nrow=2, ncol=3,
                                         align="hv") + theme(plot.margin = margin(0.25, 0.25, 0.25, 1, "cm")),
                               ggarrange(extfig9a_legend_p, geom_blank(), ncol=1, heights=c(1, 1.5)),
                               ggarrange(extfig9a_legend_a, geom_blank(), ncol=1, heights=c(1, 0.05)),
                               nrow=1,
                               widths= c(2,1,1),
                               align="h"),
                     ggarrange(
                       ggarrange(extfig9a_PHOX2A_p + extfig9a_theme , 
                                 extfig9a_PHOX2B_p + extfig9a_theme, 
                                 extfig9a_MYOD1_p + extfig9a_theme, 
                                 extfig9a_PHOX2A_a + extfig9a_theme,
                                 extfig9a_PHOX2B_a + extfig9a_theme,
                                 extfig9a_MYOD1_a + extfig9a_theme,
                                 nrow=2, ncol=3,
                                 align="hv") + theme(plot.margin = margin(0.25, 0.25, 0.25, 1, "cm")),
                       geom_blank(),
                       geom_blank(),
                       nrow=1,
                       widths= c(2,1,1)),
                     ggarrange(extfig9b + fig1_theme + theme(aspect.ratio=1), 
                               extfig9c + fig1_theme + theme(aspect.ratio=1), 
                               ncol = 2,
                               align="h",
                               labels = c("b", "c")),
                     nrow=3, 
                     ncol=1,
                     heights  = c(2, 2, 2),
                     labels = c("a", "", ""))
## Warning in as_grob.default(plot): Cannot convert object of class
## LayerInstanceLayerggprotogg into a grob.

## Warning in as_grob.default(plot): Cannot convert object of class
## LayerInstanceLayerggprotogg into a grob.

## Warning in as_grob.default(plot): Cannot convert object of class
## LayerInstanceLayerggprotogg into a grob.

## Warning in as_grob.default(plot): Cannot convert object of class
## LayerInstanceLayerggprotogg into a grob.
ggsave(extfig9, filename = "final_figures/extFig9.pdf", width=20 , height=26, units='cm', useDingbats = FALSE)
print(extfig9)

extfig10a <- readRDS('figures/dependency/deps_v_num_CLs_20q1.rds')
extfig10b <- readRDS('figures/dependency/depsLRT_v_num_CLs_20q1.rds')
extfig10c <- readRDS('figures/dependency/tfs_highlighted_enriched_deps_-0.2_20q1.rds')

extfig10a$layers[[1]]$aes_params$size <- 1
extfig10b$layers[[1]]$aes_params$size <- 1
extfig10a$layers[[2]]$aes_params$size <- 1
extfig10b$layers[[2]]$aes_params$size <- 1

extfig10 <- ggarrange(ggarrange(extfig10a + fig1_theme + theme(aspect.ratio=1), 
                                extfig10b + fig1_theme + theme(aspect.ratio=1), 
                                ncol = 2,
                                align="h",
                                labels = c("a", "b")),
                      extfig10c + fig1_theme,
                      geom_blank(),
                      nrow=3, 
                      ncol=1,
                      heights  = c(2, 3, 1),
                      labels = c("", "c"))
## Warning in as_grob.default(plot): Cannot convert object of class
## LayerInstanceLayerggprotogg into a grob.
ggsave(extfig10, filename = "final_figures/extFig10.pdf", width=20 , height=26, units='cm', useDingbats = FALSE)
print(extfig10)

source('setup.R')
## ── Attaching packages ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────── tidyverse 1.3.0 ──
## ✓ tibble  3.0.0     ✓ purrr   0.3.3
## ✓ tidyr   1.0.2     ✓ dplyr   0.8.5
## ✓ readr   1.3.1     ✓ forcats 0.5.0
## ── Conflicts ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────── tidyverse_conflicts() ──
## x dplyr::combine()   masks gridExtra::combine()
## x tidyr::extract()   masks magrittr::extract()
## x dplyr::filter()    masks stats::filter()
## x dplyr::lag()       masks stats::lag()
## x purrr::set_names() masks magrittr::set_names()
## 
## Attaching package: 'matrixStats'
## The following object is masked from 'package:dplyr':
## 
##     count
## ------------------------------------------------------------------------------
## You have loaded plyr after dplyr - this is likely to cause problems.
## If you need functions from both plyr and dplyr, please load plyr first, then dplyr:
## library(plyr); library(dplyr)
## ------------------------------------------------------------------------------
## 
## Attaching package: 'plyr'
## The following object is masked from 'package:matrixStats':
## 
##     count
## The following objects are masked from 'package:dplyr':
## 
##     arrange, count, desc, failwith, id, mutate, rename, summarise,
##     summarize
## The following object is masked from 'package:purrr':
## 
##     compact
## The following object is masked from 'package:ggpubr':
## 
##     mutate
## 
## Attaching package: 'plotly'
## The following objects are masked from 'package:plyr':
## 
##     arrange, mutate, rename, summarise
## The following object is masked from 'package:ggplot2':
## 
##     last_plot
## The following object is masked from 'package:stats':
## 
##     filter
## The following object is masked from 'package:graphics':
## 
##     layout
## 
## Attaching package: 'data.table'
## The following objects are masked from 'package:dplyr':
## 
##     between, first, last
## The following object is masked from 'package:purrr':
## 
##     transpose
## clusterProfiler v3.14.3  For help: https://guangchuangyu.github.io/software/clusterProfiler
## 
## If you use clusterProfiler in published research, please cite:
## Guangchuang Yu, Li-Gen Wang, Yanyan Han, Qing-Yu He. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS: A Journal of Integrative Biology. 2012, 16(5):284-287.
## 
## Attaching package: 'clusterProfiler'
## The following object is masked from 'package:purrr':
## 
##     simplify
## 
## Attaching package: 'scales'
## The following object is masked from 'package:purrr':
## 
##     discard
## The following object is masked from 'package:readr':
## 
##     col_factor
## 
## Attaching package: 'Seurat'
## The following object is masked from 'package:DT':
## 
##     JS
## FIt-SNE R wrapper loading.
## FIt-SNE root directory was set to /Users/ndharia/Dropbox (Partners HealthCare)/PedDep Figures/final_code
source('load_data.R')
extended_data_table_2 <- fread('Celligner/PedDep_Celligner_results.csv')
undiff_cluster <- fread('Celligner/undifferentiated_cluster_07022020.csv')

extended_data_table_2 %<>% 
  dplyr::left_join(., mf %>% dplyr::select(DepMap_ID, CCLE_name, PvA) %>% dplyr::rename(sampleID = CCLE_name), by = "sampleID") %>%
  dplyr::mutate(undifferentiated_cluster = sampleID %in% undiff_cluster$sampleID_CCLE_Name) %>%
  dplyr::select(sampleID, DepMap_ID, PvA, dplyr::everything()) %>%
  dplyr::arrange(type, DepMap_ID)

write.table(extended_data_table_2, file = "figures/tumor_cl/ExtendedDataTable2.txt", sep = "\t", row.names = F)